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GLIGE

AI Research And Development Specialist- Team Lead

London
Posted 2 days ago
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Company Description

GLIGE (www.glige.co.uk) is an early-stage start-up focused on developing AI Generative Design to industrialise construction. We aim to revolutionise how buildings and infrastructure are designed, manufactured, and delivered by developing advanced AI generative design models.

As a growing organisation, GLIGE offers the chance to help shape its technology, culture, and product strategy from the start. A mix of salary and equity can be awarded for the right candidate.

Role Description

We are seeking an AI scientist to co-lead the design, development, and deployment of an AI generative design system for the industrialisation of construction. On a day-to-day basis, you will architect core Graph-based (GNN) and PDE-based (PNN) AI models, build and iterate early AI prototypes at speed, and translate early users’ feedback into technical roadmaps.

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

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Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Qualifications

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  • Experience with Graph AI models, including Graph Neural Networks, and/or Physics-constrained neural networks, including Partial Differential Equations, demonstrated through research publications or direct working experience.
  • Passion and desire to resolve real-world problems, not just research. Industry expertise is less relevant (construction or pharma/Clinical).
  • Exceptional coding skills with a strong command of modern software practice, including PyTorch.
  • A PhD in a relevant field (Computer Science, Physics, Applied Mathematics, Machine Learning, Computational Science) with a strong foundation in GNN, Diffusion models, and PDE. A Master’s in the above discipline with 3-7 years of direct work experience on GNN, Diffusion models, and physics-informed neural networks can be considered.
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Skills

Graph Neural Networks
Physics-constrained Neural Networks
Partial Differential Equations
PyTorch
Diffusion Models
AI Generative Design
Software Practice
Graph AI
Machine Learning
Computational Science
Applied Mathematics
Physics
Computer Science

Location

London, England, United Kingdom

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